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nnUNet_results/Dataset001_Prostate158/inference_information.json

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+{
+    "all_results": {
+        "nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres": 0.7910807565880633
+    },
+    "best_model_or_ensemble": {
+        "postprocessing_file": "nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/postprocessing.pkl",
+        "result_on_crossval_post_pp": 0.7910858878327467,
+        "result_on_crossval_pre_pp": 0.7910807565880633,
+        "selected_model_or_models": [
+            {
+                "configuration": "3d_fullres",
+                "plans_identifier": "nnUNetPlans",
+                "trainer": "nnUNetTrainer_20epochs"
+            }
+        ],
+        "some_plans_file": "nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/plans.json"
+    },
+    "considered_models": [
+        {
+            "configuration": "3d_fullres",
+            "plans": "nnUNetPlans",
+            "trainer": "nnUNetTrainer_20epochs"
+        }
+    ],
+    "dataset_name_or_id": "Dataset001_Prostate158",
+    "ensembling_allowed": false,
+    "folds": [
+        0
+    ]
+}

nnUNet_results/Dataset001_Prostate158/inference_instructions.txt

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+***Run inference like this:***
+
+nnUNetv2_predict -d Dataset001_Prostate158 -i INPUT_FOLDER -o OUTPUT_FOLDER -f  0 -tr nnUNetTrainer_20epochs -c 3d_fullres -p nnUNetPlans
+
+***Once inference is completed, run postprocessing like this:***
+
+nnUNetv2_apply_postprocessing -i OUTPUT_FOLDER -o OUTPUT_FOLDER_PP -pp_pkl_file nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/postprocessing.pkl -np 8 -plans_json nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/plans.json

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nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/dataset.json

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+{
+    "name": "Prostate158",
+    "description": "Prostate cancer segmentation dataset",
+    "channel_names": {
+        "0": "T2"
+    },
+    "labels": {
+        "background": 0,
+        "prostate_inner": 1,
+        "prostate_outer": 2
+    },
+    "numTraining": 139,
+    "numTest": 19,
+    "file_ending": ".nii.gz"
+}

nnUNet_results/Dataset001_Prostate158/nnUNetTrainer_20epochs__nnUNetPlans__3d_fullres/crossval_results_folds_0/plans.json

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+{
+    "dataset_name": "Dataset001_Prostate158",
+    "plans_name": "nnUNetPlans",
+    "original_median_spacing_after_transp": [
+        3.0,
+        0.4017857015132904,
+        0.4017857015132904
+    ],
+    "original_median_shape_after_transp": [
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+        270
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+    "image_reader_writer": "SimpleITKIO",
+    "transpose_forward": [
+        0,
+        1,
+        2
+    ],
+    "transpose_backward": [
+        0,
+        1,
+        2
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+    "configurations": {
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+            "preprocessor_name": "DefaultPreprocessor",
+            "batch_size": 32,
+            "patch_size": [
+                320,
+                320
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+            "median_image_size_in_voxels": [
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+                270.0
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+                false
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+}

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